Computational Science and Engineering (CSE) is a discipline devoted to the study and advancement of computational methods and data analysis techniques to analyze and understand natural and engineered systems. CSE is inherently interdisciplinary, and integrates concepts and principles from computer science, mathematics, science, and engineering to define a new, cohesive body of knowledge that is rapidly changing. It solves real-world problems in science, engineering, health, and social domains, by using high-performance computing, modeling and simulation, and large-scale Big Data analytics. Our research enables breakthroughs in scientific discovery and engineering practice.
CSE research at Georgia Tech spans many areas. For example, research in high performance computing improves the efficiency, reliability and speed of algorithms, software, tools and applications running on a variety of architectures. Machine learning research explores the construction and study of algorithms that build models and make data-driven predictions or decisions. Data science and engineering techniques develop new methods that transform large and complex data sets into value. Data visualization requires creating a representation of data, interactively manipulating and querying it, and traversing enormous data sets ranging from terabytes to petabytes. Cybersecurity encompasses a range of analytic techniques that rely on high performance computing algorithms to secure the confidentiality, integrity, and availability of data.
The School of CSE is a diverse, interdisciplinary innovation ecosystem composed of award-winning faculty, researchers, and students. We are creating future leaders who keep pace with and solve the most challenging problems in science, engineering, health, and social domains.
Read the CSE Annual Report for more information.